Dr Eftychia Solea

Eftychia Solea
PhD

Lecturer in Statistics

School of Mathematical Sciences
Queen Mary University of London
Google Scholar

Research

causal inference, dimension reduction, functional data analysis, graphical models, nonparametric statistics, object-oriented data analysis

Interests

My primary research interest lies in developing statistical methodologies for analyzing complex random data objects, which can be interpreted as random elements in topological or metric spaces. These types of data frequently arise in fields such as medical imaging. My aim is to contribute to the theoretical underpinnings of these methods and to design efficient algorithms for their practical application.

To date, my research has largely focused on Functional Data Analysis, for analysing samples of curves (mathematical functions). Key areas of my work include graphical models, dimension reduction, quantile regression, causal inference for functional data, and distributional data analysis, where the data comprises samples of distributions or densities.

Publications

solid heart iconPublications of specific relevance to the Centre for Probability, Statistics and Data Science

2023

Relevant PublicationSolea E and Al Hajj R (2023). High-dimensional rank-based graphical models for non-Gaussian functional data. Statistics, Taylor & Francis vol. 57 (2), 388-422.  
04-03-2023
Relevant PublicationSheng T, Li B and Solea E (2023). On skewed Gaussian graphical models. Journal of Multivariate Analysis, Elsevier vol. 194 
01-03-2023

2022

Relevant PublicationSolea E and Dette H (2022). Nonparametric and high-dimensional functional graphical models. Electronic Journal of Statistics, Institute of Mathematical Statistics vol. 16 (2) 
01-01-2022

2020

Relevant PublicationSolea E and Li B (2020). Copula Gaussian Graphical Models for Functional Data. Journal of the American Statistical Association, Taylor & Francis vol. 117 (538), 781-793.  
16-10-2020

2018

Relevant PublicationLi B and Solea E (2018). A Nonparametric Graphical Model for Functional Data With Application to Brain Networks Based on fMRI. Journal of the American Statistical Association, Taylor & Francis vol. 113 (524), 1637-1655.  
02-10-2018

2017

Relevant PublicationSolea E, Li B and Slavković A (2017). Statistical learning on emerging economies. Journal of Applied Statistics, Taylor & Francis vol. 45 (3), 487-507.  
31-01-2017